Title :
A radial basis function framework for various adaptive fuzzy equalizers used in mobile cellular channels
Author :
Raveendranathan, K.C.
Author_Institution :
Dept. of Electron. & Commun. Eng., Gov. Eng. Coll., Thiruvananthapuram
Abstract :
The radial basis function (RBF) based neural networks have been successfully used to solve many non-linear problems, including that of adaptive channel equalization. In this paper, we present three different adaptive fuzzy/neuro-fuzzy channel equalizers that closely fit into the broad framework of RBF neural network based systems. We consider the type-2 fuzzy adaptive filter (FAF) based channel equalizer along with a compensatory neuro-fuzzy filter (CNFF) and the one based on an adaptive network based fuzzy inference system (ANFIS) as applied to mobile cellular channels. We establish that the above three implementations of adaptive equalizers do fit into the generic framework of radial basis function (RBF) based systems.
Keywords :
adaptive equalisers; adaptive filters; cellular radio; fuzzy set theory; inference mechanisms; radial basis function networks; telecommunication computing; wireless channels; ANFIS; adaptive channel equalization; adaptive fuzzy channel equalizers; adaptive network based fuzzy inference system; compensatory neuro-fuzzy filter; fuzzy adaptive filter; mobile cellular channels; neural networks; neuro-fuzzy channel equalizers; radial basis function framework; Adaptive equalizers; Adaptive filters; Cellular networks; Frequency; Fuzzy neural networks; Fuzzy systems; Interchannel interference; Mobile communication; Neural networks; Radial basis function networks; ANFIS; Adaptive Channel Equalizer; CNFF; Channel Equalization; FAF; LTI Channels; LTV Channels; Radial Basis Function Neural Network (RBF NN);
Conference_Titel :
TENCON 2008 - 2008 IEEE Region 10 Conference
Conference_Location :
Hyderabad
Print_ISBN :
978-1-4244-2408-5
Electronic_ISBN :
978-1-4244-2409-2
DOI :
10.1109/TENCON.2008.4766391
